These teachings relate generally to method and systems for detecting objects concealed on a body.
The task of Automatic Threat Detection (“ATD”) is to automatically sense and detect objects that may be concealed on a body and may constitute a threat. Typically, an ATD system uses some form of sensor to provide detection of objects and provide an alarm when needed. Although metallic objects can be identified using well known and ubiquitous metal detectors, the detection of non-metallic objects is more problematic and other forms of detection must be used. Some forms of ATD systems provide imaging a body and these systems must be able to distinguish discrete parts of an image or images that are likely to be objects that are classified as dangerous or as threats from those parts of the image that are likely to be benign.
One form of detection that may be used to identify non-metallic objects is the use of passive millimeter wave (“MMW”) radiation. In a passive system, the MMW radiation is detected by a MMW receiver, typically some form of MMW camera that images the body at one or more desired frequencies and provides one or more images of the body for analysis. These images are analyzed to determine the presence of non-metallic objects, in addition to any metallic ones, that may be considered to be threats. Although the prior art has used MMW radiation to detect non-metallic objects, there are several possible improvements with the prior art.
Among the problems in the prior art is that the appearance of benign parts of the subject's body often mimics that of threats in the MMW imagery. Threat-free parts of the human body do have shades of lightness and darkness in the MMW imagery. There is often no clear-cut way of deciding whether a dark region is a benign part of the body or a true threat. (Benign regions of the image that are similar to threats in appearance are termed “clutter”.) The availability of images of the subject as they move in front of the camera allows a human observer of the MMW imagery to form judgments about subtle differences in the manner in which true threats traverse the field of view vis-à-vis the progression of clutter regions.
The prior art has attempted to make similar judgments through computer algorithms by analyzing the MMW image frames one at a time and extracts candidate threat information from separate frames and then combines it by some subsequent technique of data association and tracking over time.